Sensorless effective wind speed estimation method based on unknown input disturbance observer and extreme learning machine

Energy ◽  
2019 ◽  
Vol 186 ◽  
pp. 115790 ◽  
Author(s):  
Xiaofei Deng ◽  
Jian Yang ◽  
Yao Sun ◽  
Dongran Song ◽  
Xiaoyan Xiang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Extreme Learning Machine ◽  
Disturbance Observer ◽  
Estimation Method ◽  
Unknown Input ◽  
Speed Estimation ◽  
Input Disturbance ◽  
Learning Machine

Extreme learning machine approach for sensorless wind speed estimation

Mechatronics ◽  
2016 ◽  
Vol 34 ◽  
pp. 78-83 ◽  
Author(s):  
Vlastimir Nikolić ◽  
Shervin Motamedi ◽  
Shahaboddin Shamshirband ◽  
Dalibor Petković ◽  
Sudheer Ch ◽  
...  
Keyword(s):  
Wind Speed ◽  
Extreme Learning Machine ◽  
Speed Estimation ◽  
Learning Machine

A Hybrid Short-Term Wind Speed Forecasting Model Based on Wavelet Decomposition and Extreme Learning Machine

2013 ◽  
Vol 860-863 ◽  
pp. 361-367 ◽  
Author(s):  
Yi Hui Zhang ◽  
He Wang ◽  
Zhi Jian Hu ◽  
Kai Wang ◽  
Yan Li ◽  
...  
Keyword(s):  
Wind Speed ◽  
Extreme Learning Machine ◽  
Wavelet Decomposition ◽  
Forecasting Model ◽  
Short Term ◽  
Machine Model ◽  
Wind Speed Prediction ◽  
Speed Prediction ◽  
Learning Machine ◽  
Short Term Prediction

This paper studied the short-term prediction of wind speed by means of wavelet decomposition and Extreme Learning Machine. Wind speed signal was decomposed into several sequences by wavelet decomposition to reduce the non-stationary. Secondly, the phase space reconstructed was used to mine sequences characteristics, and then an improved extreme learning machine model of each component was established. Finally, the results of each component forecast superimposed to get the final result. The simulation result verified that the hybrid model effectively improved the wind speed prediction accuracy.

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